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Notes for a class on electrochemical engineering, including fundamental information about electrochemical cells and their...
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Notes for a class on electrochemical engineering, including fundamental information about electrochemical cells and their related thermodynamics, kinetics, and mass transfer; plus applications such as lithium ion batteries, electrode fabrication, fuel cells, and the hydrogen economy.

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This video was recorded at IEEE International Conference on Multimedia & Expo (ICME), Melbourne 2012. In 1995, Mark Weiser...
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This video was recorded at IEEE International Conference on Multimedia & Expo (ICME), Melbourne 2012. In 1995, Mark Weiser and John Seeley Brown said that computers would enter society in 3 stages. The Mainframe Era was followed by the Personal Computer Era. They predicted that the internet and distributed computing would lead to an era of Ubiquitous Computing. Some say that it has, but what we now call UC is not what Weiser and Brown described. It is true that each person now uses many computers, instead of the other way around, but they did not just define UC by the human: computer ratio. "The most potentially interesting, challenging and profound change implied by the ubiquitous computing era is a focus on calm." Calm Technology is based on the two ways that humans process information. Trying to focus on more than one thing at once is stressful, but humans can take in much more information if it is presented peripherally; in a way that allows the individual to judge whether or not to give it more attention. Basic physiology and neuroanatomy show that we naturally examine things closely while at the same time using other senses to keep track of subtle changes in our environment, warning us when the peripheral becomes important. What's more, the process of plucking things from the periphery, examining them and then deciding how to resort them is a comforting activity. It makes us feel at home and in control. Ubiquitous Computing is everywhere now (if you'll pardon the pun) but Calm Technology has been all but abandoned because it is harder to design and implement than traditional multi‐media interaction. So, instead of deliberate calm, we have constant text message alerts, ring tones and email pop‐ups demanding the immediate attention of everyone within earshot. Imagine instead that your cell phone would subtly let you know who is trying to reach you without pulling your attention away from the task at hand. It could be as gentle as familiar footsteps drawing close or the hint of a smile on your touchscreen. Hardware and software are now more than good enough, and rich multimedia can be customised, stored, accessed and processed quickly and cheaply. It is time for Human Computer Interaction based on rich and textured interfaces; interaction that is less like a series of screaming emergencies fighting for our attention, and more like a walk in the woods. It is time for Calm Technology. References: Weiser and Brown, "Designing Calm Technology״, 1995, Powergrid Journal, 1,1. (Available from: http://sandbox.xerox.com/hypertext/weiser/calmtech/calmtech. htm)

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This video was recorded at 14th International Conference on Artificial Intelligence and Statistics (AISTATS), Ft. Lauderdale...
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This video was recorded at 14th International Conference on Artificial Intelligence and Statistics (AISTATS), Ft. Lauderdale 2011. The standard compressive sensing (CS) aims to recover sparse signal from single measurement vector which is known as SMV model. By contrast, recovery of sparse signals from multiple measurement vectors is called MMV model. In this paper, we consider the recovery of jointly sparse signals in the MMV model where multiple signal measurements are represented as a matrix and the sparsity of signal occurs in common locations. The sparse MMV model can be formulated as a matrix (2; 1)-norm minimization problem, which is much more difficult to solve than the l1-norm minimization in standard CS. In this paper, we propose a very fast algorithm, called MMV-ADM, to solve the jointly sparse signal recovery problem in MMV settings based on the alternating direction method (ADM). The MMV-ADM alternately updates the recovered signal matrix, the Lagrangian multiplier and the residue, and all update rules only involve matrix or vector multiplications and summations, so it is simple, easy to implement and much faster than the state-of-the-art method MMVprox. Numerical simulations show that MMV-ADM is at least dozens of times faster than MMVprox with comparable recovery accuracy.

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This video was recorded at Transnational ICT and Security Technology Opportunities, Ljubljana 2007. The andEuros company is...
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This video was recorded at Transnational ICT and Security Technology Opportunities, Ljubljana 2007. The andEuros company is active in electronics and software research and development to provide complete solutions on system architecture, sensors, sensor networks, mixed signal hardware designs, distributed software and hardware platforms, embedded systems, FPGA/VHDL system-on-chip design, powerline communications and sensor protocols.

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This tutorial will cover the design of a simple system-on-a-chip in VHDL, with an emphasis on the development and simulation...
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This tutorial will cover the design of a simple system-on-a-chip in VHDL, with an emphasis on the development and simulation of a testbench for the mu0 microprocessor. The mu0 and its associated RAM is treated as black boxes, and a testbench is developed around them. The VHDL design of the mu0 can be downloaded from the webpage.

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